conduit AGENTS.md

Repository instructions for Conduit, a server that connects AI agents to Phabricator and Phorge, tools for tasks, code reviews, repositories, files, and teams.

In plain words
What is it for?
Working with project tasks, code reviews, commits, repository files, uploads and downloads, users, projects, and the server's system interface.
Why use it?
They explain the server structure, available services, and development process so changes fit the existing design.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/cortex-app/conduit/agents-md
Clone the repo
git clone --depth 1 https://github.com/cortex-app/conduit

Made for: Codex, OpenCode.

Per session 2,383 This file is loaded in full into every session.
When invoked 2,383 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.02383 $0.02383
Opus 5 $0.01192 $0.01192
Sonnet 5 $0.00477 $0.00477
Haiku 4.5 $0.00238 $0.00238

Measured 2d ago against content hash e7b6d334516c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

conduit AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 256 lines

How it starts

The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Conduit MCP Server - AI Development Guide

Architecture Overview

Conduit is a Model Context Protocol (MCP) server that provides seamless integration with Phabricator and Phorge APIs through a modular client pattern with unified entry points.

Core Architecture

  • Main Server (src/conduit.py): FastMCP-based server with dual transport modes (stdio/HTTP-SSE)
  • Unified Client (src/client/unified.py): Enhanced client with caching, retries, and token optimization
  • Modular Clients (src/client/*.py): Specialized clients for different Phabricator APIs

Supported APIs

  • Maniphest: Task management (search, create, edit tasks, get transaction history)
  • Differential: Code review (search, create, manage revisions)
  • Diffusion: Repository management (search, browse, commits, file content with base64 decoding)
  • File: File management (search, upload, download)
  • User: User management (information, queries)
  • Project: Project management (search, members, workboards)
  • Conduit: System interface (ping, capabilities, info)

Development Workflow

Environment Setup

This project uses uv virtual environment. Before executing any Python code, activate the Python virtual environment first:

# Since this is a Phabricator MCP Server, you may set environment variables
# Example environment variables (replace with your actual values):
# export PHABRICATOR_TOKEN="your-32-character-token"
# export PHABRICATOR_URL="https://your-phabricator-instance.com/api/"
# export PHABRICATOR_PROXY="socks5://127.0.0.1:1080"  # Optional
# export PHABRICATOR_DISABLE_CERT_VERIFY=1  # Optional (security risk)

# Actual execution with environment variables:
PHABRICATOR_TOKEN="your-32-character-token" \
PHABRICATOR_URL="https://your-phabricator-instance.com/api/" \
PHABRICATOR_PROXY="socks5://127.0.0.1:1080" \
PHABRICATOR_DISABLE_CERT_VERIFY=1 \
source venv/bin/activate && python your_script.py

# Example, actual name may changed
source venv/bin/activate && uv pip xxx
source xxx && python xxx

Read the full file on GitHub · 256 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 256 lines · 2,383 tokens per session scan A e7b6d334516c

Subscribe to this mod's changes

conduit AGENTS.md is an instructions file published in the GitHub repository cortex-app/conduit (7 stars, last pushed 7mo ago), licensed MIT. It adds 2,383 tokens to every session, about $0.0119 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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